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Global Wheat Detection

Sayak Paul

Sayak Paul

Kolkata, West Bengal

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  • 0 Collaborators

Showcases the use of deep learning to detect wheat heads from crops. ...learn more

Project status: Under Development

Internet of Things, Artificial Intelligence

Intel Technologies
Intel Python

Code Samples [1]

Overview / Usage

The project is based on this Kaggle Competition: https://www.kaggle.com/c/global-wheat-detection. The task is to detect wheat heads from outdoor images of wheat plants, including wheat datasets from around the globe. Using worldwide data, you will focus on a generalized solution to estimate the number and size of wheat heads. To better gauge the performance for unseen genotypes, environments, and observational conditions, the training dataset covers multiple regions. You will use more than 3,000 images from Europe (France, UK, Switzerland) and North America (Canada). The test data includes about 1,000 images from Australia, Japan, and China.

Methodology / Approach

Uses deep learning-based object detection models like Faster R-CNN for the detection task.

Technologies Used

  • TensorFlow Object Detection API

Repository

https://github.com/sayakpaul/Global-Wheat-Detection/

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